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Modelling catchment inflows into Lake Victoria: uncertainties in rainfall-runoff modelling for the Nzoia River
Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, LUVAL.
Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, LUVAL.
2011 (English)In: Hydrological Sciences Journal, ISSN 0262-6667, Vol. 56, no 7, 1210-1226 p.Article in journal (Refereed) Published
Abstract [en]

Climate and soil characteristics vary considerably around the Lake Victoria basin resulting in high spatial and temporal variability in catchment inflows. However, data for estimating the inflows are usually sparsely distributed and error-prone. Therefore, modelled estimates of the flows are highly uncertain, which could explain early difficulties in reproducing the lake water balance. The aim of this study was to improve the estimates of catchment flow to Lake Victoria. The WASMOD model was applied to the Nzoia River, one of the major tributaries to Lake Victoria. Uncertainty was assessed within the GLUE framework. During calibration, log-transformation was performed on both simulated and observed flows. The results showed that, despite its simple structure, WASMOD produces acceptable results for the basin. For a Nash-Sutcliffe efficiency (NS) threshold of 0.6, the percentage of observations bracketed by simulations (POBS) was 74%, the average relative interval length (ARIL) was 0.93, and the maximum NS value was 0.865. The residuals were shown to be homoscedastic, normally distributed and nearly independent. When the NS threshold was increased to 0.8, POBS decreased to 54% with an improvement of ARIL to 0.49, highlighting the effect of the subjective choice of likelihood threshold.

Place, publisher, year, edition, pages
2011. Vol. 56, no 7, 1210-1226 p.
Keyword [en]
rainfall-runoff modelling, GLUE, Nash-Sutcliffe efficiency, Nzoia River, Lake Victoria, WASMOD, uncertainty
National Category
Oceanography, Hydrology, Water Resources
URN: urn:nbn:se:uu:diva-260062DOI: 10.1080/02626667.2011.610323ISI: 000297289600009OAI: oai:DiVA.org:uu-260062DiVA: diva2:846173
Available from: 2015-08-14 Created: 2015-08-14 Last updated: 2015-08-14Bibliographically approved

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